The present invention generally relates to radio frequency signals, and particularly relates to received signal filtering.
Wireless receiver performance depends on the receiver's ability to discriminate between received signals within the spectrum of interest and those signals lying “out-of-band.” Interference with desired signal reception becomes particularly problematic when the interfering signal or signals are relatively close in frequency to the desired signal.
While all types of RF communication systems are susceptible to varying types of signal interference at the receiver, certain types of systems have heightened susceptibilities. For example, communication system air interfaces based on the Wideband Code Division Multiple Access (W-CDMA) standards use signals that are oftentimes much wider in bandwidth than the other signals with which they must coexist. Wireless communication systems based on the Global System for Mobile Communication (GSM) standards and operating in the 1900 MHz Personal Communication Systems (PCS) band in the International Telecommunication Union (ITU) Region 2 represent a significant potential source of interference for W-CDMA systems. Where W-CDMA and GSM wireless communication networks coexist, the GSM systems place relatively narrowband signals at frequencies close to W-CDMA signal frequencies.
Because W-CDMA receivers are designed to receive wideband signals, designing receiver filters that pass the wideband signal of interest while simultaneously rejecting narrowband signals at the edge of the wideband signal presents significant challenges. These challenges extend beyond the framework of W-CDMA receivers, and it is generally understood that designing pass-band filters with sharp out-of-band cutoffs represents a complex and careful balancing of cost, complexity, and performance.
Existing approaches to receive signal filtering include the use of surface acoustic wave (SAW) filters, analog baseband filters, and various approaches to digital filtering. SAW devices can provide excellent filtering performance, but at the cost of added expense and physical size. The same shortcomings are largely true of other analog-domain signal filtering. Digital filtering, such as by Finite Impulse Response (FIR) filtering also offers decent performance, but as filter performance increases, so too does processing complexity and power consumption.